the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A Global Gridded Dataset for Cloud Vertical Structure from Combined CloudSat and CALIPSO Observations
William Bertrand
Jennifer E. Kay
John Haynes
Gijs de Boer
Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally-gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product, a globally-gridded (level 3S) community data product summarizing geometrical profiles (-GEOPROF) of hydrometeor occurrence from combined (-COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level 2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10 degree spatial resolution and monthly and seasonal temporal resolution. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as a surface-based dataset, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud-climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.
- Preprint
(1615 KB) - Metadata XML
- BibTeX
- EndNote
William Bertrand et al.
Status: open (extended)
-
RC1: 'Comment on essd-2023-265', Anonymous Referee #1, 14 Aug 2023
reply
The manuscript delivers a comprehensive exploration into the creation of a global dataset that delineates the vertical structure of clouds, harnessing the combined observational capabilities of CloudSat and CALIPSO. The attempt to integrate data from these two satellites is both ambitious and timely, providing a unified perspective on cloud distribution, altitude, and overall cloud architecture. The result is a dataset that could become an invaluable tool for climatologists, meteorologists, and researchers working in atmospheric sciences. While the paper offers an impressive scope, a few suggestions for enhancement are presented below:
Specific Comments:
- In Figures 6 and 9, the portrayal of global cloud patterns and anomalies is instructive. However, it would enhance the paper's depth to delve into more elaborations about regional variations, the role of seasons, and potential correlations with established climatic phenomena. In addition, the authors may discuss whether the datasets can potentially illuminate some new insights into cloud characteristics.
- It's laudable that the authors have illuminated potential discrepancies and constraints within the dataset in the error analysis section. Nonetheless, a more expansive discussion on the inherent uncertainties, especially when navigating regions marked by different topographies or areas known for complex cloud systems, would be invaluable.
- For clarity and utility, it might be beneficial to delineate exact numbers related to the uncertainties inherent in datasets across different global regions. Such specificity would aid users in gauging the reliability of the data in diverse contexts.
- One notable observation is the narrow focus on dataset evaluation at Utqiagvik, Alaska, despite its global ambit. Given the universal scope of the dataset, is there a reason for concentrating evaluation efforts in this isolated region? With resources like the ARM program, which boasts a spectrum of global observatories, a broader evaluation could reinforce the dataset's credibility across multiple geographies.
Citation: https://doi.org/10.5194/essd-2023-265-RC1
William Bertrand et al.
Data sets
3S-GEOPROF-COMB: A Global Gridded Dataset for Cloud Vertical Structure from combined CloudSat and CALIPSO observations William Bertrand, Jennifer E. Kay, John Haynes, and Gijs de Boer https://zenodo.org/record/8057791
William Bertrand et al.
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
276 | 100 | 15 | 391 | 9 | 9 |
- HTML: 276
- PDF: 100
- XML: 15
- Total: 391
- BibTeX: 9
- EndNote: 9
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1